{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "import numpy as np\n",
    "from numba import jit\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import mean_absolute_error as MAE\n",
    "import psutil\n",
    "import os\n",
    "\n",
    "plt.rcParams['font.sans-serif']=['SimHei']  # 用来正常显示中文标签\n",
    "plt.rcParams['axes.unicode_minus']=False # 用来正常显示负号\n",
    "plt.style.use('fivethirtyeight') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6442892, 5)"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取全部数据\n",
    "df = pd.read_table('../GIS_LSH_VE_CF/data/Gowalla_totalCheckins.txt',sep=\"\\t\",names=['user_id','check-in time','latitude','longitude','location id'],encoding='latin-1',engine='python')\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def distribution_scatter(df):\n",
    "    '''\n",
    "        传入df数据结构，绘制经纬度散点图\n",
    "    '''\n",
    "    plt.figure(1 , figsize = (15 , 6))\n",
    "    plt.scatter(x = 'latitude' , y = 'longitude' , data = df ,\n",
    "                    s = 80 , alpha = 0.5 )\n",
    "    plt.xlabel('latitude' ), plt.ylabel('longitude') \n",
    "    plt.title('Latitude and longitude distribution')\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_scatter(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据规模为:6442892条,用户有:107092个,打卡地点有:1280969个\n"
     ]
    }
   ],
   "source": [
    "# 查看用户和打卡地点\n",
    "user_num = df['user_id'].unique().shape[0]\n",
    "loc_num = df['location id'].unique().shape[0]\n",
    "print(\"数据规模为:{0}条,用户有:{1}个,打卡地点有:{2}个\".format(df.shape[0],user_num,loc_num))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 进行数据抽取，注意：所有数据集都要把第一行手动删除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 一个用户抽取两条信息，抽取12000条数据,共计6000个用户\n",
    "user_id_list = df['user_id'].unique()\n",
    "data = df.iloc[:12000]\n",
    "for i in range(12000):\n",
    "    user_id = user_id_list[int(i/2)] # 每个用户取两条信息\n",
    "    print(user_id)\n",
    "    data.iloc[i] = df[df['user_id']==user_id].iloc[i%2] # 根据取余运算，取第0行和第1行\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_scatter(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30.235909</td>\n",
       "      <td>-97.795140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>30.269103</td>\n",
       "      <td>-97.749395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48.863379</td>\n",
       "      <td>2.333329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>48.863379</td>\n",
       "      <td>2.333329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>34.043023</td>\n",
       "      <td>-118.267157</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    latitude   longitude\n",
       "0  30.235909  -97.795140\n",
       "0  30.269103  -97.749395\n",
       "1  48.863379    2.333329\n",
       "1  48.863379    2.333329\n",
       "2  34.043023 -118.267157"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将user_id作为索引，删除没用的信息\n",
    "data.index = data['user_id']\n",
    "del data['check-in time']\n",
    "del data['user_id']\n",
    "del data['location_id']\n",
    "data.to_csv('../GIS_LSH_VE_CF/data/data.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 随机选取1000个用户作为测试集，剩下的作为训练集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\zwt\\AppData\\Local\\Temp\\ipykernel_6772\\1658871224.py:3: DeprecationWarning: Sampling from a set deprecated\n",
      "since Python 3.9 and will be removed in a subsequent version.\n",
      "  test_id = random.sample(index,1000)\n",
      "C:\\Users\\zwt\\AppData\\Local\\Temp\\ipykernel_6772\\1658871224.py:8: FutureWarning: Passing a set as an indexer is deprecated and will raise in a future version. Use a list instead.\n",
      "  train_data = data.loc[train_id]\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "index = set(data.index)\n",
    "test_id = random.sample(index,1000)\n",
    "test_data = data.loc[test_id]\n",
    "test_data.to_csv('../GIS_LSH_VE_CF/data/test.csv')\n",
    "\n",
    "train_id = index-set(test_id)\n",
    "train_data = data.loc[train_id]\n",
    "train_data.to_csv('../GIS_LSH_VE_CF/data/train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_scatter(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "distribution_scatter(train_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 构建用户坐标矩阵，便于之后训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>60.505012</td>\n",
       "      <td>-195.544535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>97.726758</td>\n",
       "      <td>4.666657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>68.086046</td>\n",
       "      <td>-236.534314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>75.565209</td>\n",
       "      <td>-244.815216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>60.538206</td>\n",
       "      <td>-195.498791</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    latitude   longitude\n",
       "0  60.505012 -195.544535\n",
       "1  97.726758    4.666657\n",
       "2  68.086046 -236.534314\n",
       "4  75.565209 -244.815216\n",
       "7  60.538206 -195.498791"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "user_mx = data.groupby(data.index).sum()\n",
    "user_mx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将用户的经纬度转换为list存储\n",
    "data_latitude = data.groupby(data.index).latitude.apply(list)\n",
    "data_longitude = data.groupby(data.index).longitude.apply(list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>user_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[30.2359091167, 30.2691029532]</td>\n",
       "      <td>[-97.7951395833, -97.7493953705]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[48.86337875, 48.86337875]</td>\n",
       "      <td>[2.333328717, 2.333328717]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[34.0430230998, 34.0430230998]</td>\n",
       "      <td>[-118.2671570778, -118.2671570778]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[37.7826046833, 37.7826046833]</td>\n",
       "      <td>[-122.4076080167, -122.4076080167]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[40.761176868, 40.761176868]</td>\n",
       "      <td>[-73.9868709323, -73.9868709323]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                               latitude                           longitude\n",
       "user_id                                                                    \n",
       "0        [30.2359091167, 30.2691029532]    [-97.7951395833, -97.7493953705]\n",
       "1            [48.86337875, 48.86337875]          [2.333328717, 2.333328717]\n",
       "2        [34.0430230998, 34.0430230998]  [-118.2671570778, -118.2671570778]\n",
       "4        [37.7826046833, 37.7826046833]  [-122.4076080167, -122.4076080167]\n",
       "5          [40.761176868, 40.761176868]    [-73.9868709323, -73.9868709323]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将用户的经纬度化为数组存储，以用户为索引，便于之后的计算\n",
    "user_mx['user_id'] = user_mx.index\n",
    "def latitude(userId):\n",
    "    return data_latitude[userId]\n",
    "\n",
    "def longitude(userId):\n",
    "    return data_longitude[userId]\n",
    "user_mx['latitude'] = user_mx['user_id'].apply(latitude)\n",
    "user_mx['longitude'] = user_mx['user_id'].apply(longitude)\n",
    "del user_mx['location id']\n",
    "del user_mx['user_id']\n",
    "user_mx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_mx.to_csv('../GIS_LSH_VE_CF/data/user_mx.csv')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 生成恶意数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "original_data = pd.read_table('../GIS_LSH_VE_CF/data/train.csv',sep=\",\",names=['latitude','longitude'],encoding='latin-1',engine='python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12.653"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(random.uniform(0,90),3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\zwt\\AppData\\Local\\Temp\\ipykernel_8032\\2273222509.py:11: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  attack_data['id'] = user_id\n",
      "C:\\Users\\zwt\\AppData\\Local\\Temp\\ipykernel_8032\\2273222509.py:12: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  attack_data['longitude'] = attack_long\n",
      "C:\\Users\\zwt\\AppData\\Local\\Temp\\ipykernel_8032\\2273222509.py:13: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  attack_data['latitude'] = attack_la\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "train_data = original_data[0:5000]\n",
    "attack_data = train_data\n",
    "user_id, attack_la, attack_long = [], [], []\n",
    "temp = 16000\n",
    "for i in range(5000): # 用户索引和经纬度进行随机生成\n",
    "    user_id.append(int(temp/2))\n",
    "    attack_la.append(round(random.uniform(0,90),3))\n",
    "    attack_long.append(round(random.uniform(0,180),3))\n",
    "    temp = temp + 1\n",
    "attack_data['id'] = user_id\n",
    "attack_data['longitude'] = attack_long\n",
    "attack_data['latitude'] = attack_la\n",
    "attack_data = attack_data.set_index('id')\n",
    "attack_data.to_csv(\"../GIS_LSH_VE_CF/data/attack_data.csv\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 用户攻击矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8000</th>\n",
       "      <td>155.723</td>\n",
       "      <td>114.392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8001</th>\n",
       "      <td>117.367</td>\n",
       "      <td>177.843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8002</th>\n",
       "      <td>111.525</td>\n",
       "      <td>139.179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8003</th>\n",
       "      <td>63.126</td>\n",
       "      <td>153.208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8004</th>\n",
       "      <td>95.165</td>\n",
       "      <td>246.101</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      latitude  longitude\n",
       "8000   155.723    114.392\n",
       "8001   117.367    177.843\n",
       "8002   111.525    139.179\n",
       "8003    63.126    153.208\n",
       "8004    95.165    246.101"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "attack_data = pd.read_table('../GIS_LSH_VE_CF/data/attack_data.csv',sep=\",\",names=['latitude','longitude'],encoding='latin-1',engine='python')\n",
    "attack_user_mx = attack_data.groupby(attack_data.index).sum()\n",
    "attack_user_mx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 将用户的经纬度转换为list存储\n",
    "attack_data_latitude = attack_data.groupby(attack_data.index).latitude.apply(list)\n",
    "attack_data_longitude = attack_data.groupby(attack_data.index).longitude.apply(list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>user_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8000</th>\n",
       "      <td>155.723</td>\n",
       "      <td>114.392</td>\n",
       "      <td>8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8001</th>\n",
       "      <td>117.367</td>\n",
       "      <td>177.843</td>\n",
       "      <td>8001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8002</th>\n",
       "      <td>111.525</td>\n",
       "      <td>139.179</td>\n",
       "      <td>8002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8003</th>\n",
       "      <td>63.126</td>\n",
       "      <td>153.208</td>\n",
       "      <td>8003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8004</th>\n",
       "      <td>95.165</td>\n",
       "      <td>246.101</td>\n",
       "      <td>8004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10495</th>\n",
       "      <td>91.199</td>\n",
       "      <td>196.789</td>\n",
       "      <td>10495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10496</th>\n",
       "      <td>166.158</td>\n",
       "      <td>202.469</td>\n",
       "      <td>10496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10497</th>\n",
       "      <td>81.083</td>\n",
       "      <td>150.898</td>\n",
       "      <td>10497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10498</th>\n",
       "      <td>139.879</td>\n",
       "      <td>230.024</td>\n",
       "      <td>10498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10499</th>\n",
       "      <td>93.010</td>\n",
       "      <td>189.917</td>\n",
       "      <td>10499</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2500 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       latitude  longitude  user_id\n",
       "8000    155.723    114.392     8000\n",
       "8001    117.367    177.843     8001\n",
       "8002    111.525    139.179     8002\n",
       "8003     63.126    153.208     8003\n",
       "8004     95.165    246.101     8004\n",
       "...         ...        ...      ...\n",
       "10495    91.199    196.789    10495\n",
       "10496   166.158    202.469    10496\n",
       "10497    81.083    150.898    10497\n",
       "10498   139.879    230.024    10498\n",
       "10499    93.010    189.917    10499\n",
       "\n",
       "[2500 rows x 3 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "attack_user_mx['user_id'] = attack_user_mx.index\n",
    "attack_user_mx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8000</th>\n",
       "      <td>[77.147, 78.576]</td>\n",
       "      <td>[71.688, 42.704]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8001</th>\n",
       "      <td>[42.196, 75.171]</td>\n",
       "      <td>[159.144, 18.699]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8002</th>\n",
       "      <td>[76.837, 34.688]</td>\n",
       "      <td>[97.09, 42.089]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8003</th>\n",
       "      <td>[18.397, 44.729]</td>\n",
       "      <td>[105.016, 48.192]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8004</th>\n",
       "      <td>[27.46, 67.705]</td>\n",
       "      <td>[163.042, 83.059]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              latitude          longitude\n",
       "8000  [77.147, 78.576]   [71.688, 42.704]\n",
       "8001  [42.196, 75.171]  [159.144, 18.699]\n",
       "8002  [76.837, 34.688]    [97.09, 42.089]\n",
       "8003  [18.397, 44.729]  [105.016, 48.192]\n",
       "8004   [27.46, 67.705]  [163.042, 83.059]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 将用户的经纬度化为数组存储，以用户为索引，便于之后的计算\n",
    "attack_user_mx['user_id'] = attack_user_mx.index\n",
    "def latitude(userId):\n",
    "    return attack_data_latitude[userId]\n",
    "\n",
    "def longitude(userId):\n",
    "    return attack_data_longitude[userId]\n",
    "attack_user_mx['latitude'] = attack_user_mx['user_id'].apply(latitude)\n",
    "attack_user_mx['longitude'] = attack_user_mx['user_id'].apply(longitude)\n",
    "del attack_user_mx['user_id']\n",
    "attack_user_mx.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "attack_user_mx.to_csv(\"../GIS_LSH_VE_CF/data/attack_user_mx\")"
   ]
  }
 ],
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